OpenRaiser/Intern-Atlas huggingface dataset:
Detecting Malicious Code by Exploiting Dependencies of System-call Groups
Venue: arXiv cs.CR 2014
Year: 2014

In this paper we present an elaborated graph-based algorithmic technique for efficient malware detection. More precisely, we utilize the system-call dependency graphs (or, for short ScD graphs), obtained by capturing taint analysis traces and a set of various similarity metrics in order to detect whether an unknown test sample is a malicious or a benign one. For the sake of generalization, we decide to empower our model against strong mutations by applying our detection technique on a weighted directed graph resulting from ScD graph after grouping disjoint subsets of its vertices. Additionally, we have developed a similarity metric, which we call NP-similarity, that combines qualitative, quantitative, and relational characteristics that are spread among the members of known malware families to archives a clear distinction between graph-representations of malware and the ones of benign software. Finally, we evaluate our detection model and compare our results against the results achieved by a variety of techniques proving the potentials of our model.
Index Coding with Coded Side-Information
Venue: arXiv cs.IT 2014
Year: 2014

This letter investigates a new class of index coding problems. One sender broadcasts packets to multiple users, each desiring a subset, by exploiting prior knowledge of linear combinations of packets. We refer to this class of problems as index coding with coded side-information. Our aim is to characterize the minimum index code length that the sender needs to transmit to simultaneously satisfy all user requests. We show that the optimal binary vector index code length is equal to the minimum rank (minrank) of a matrix whose elements consist of the sets of desired packet indices and side- information encoding matrices. This is the natural extension of matrix minrank in the presence of coded side information. Using the derived expression, we propose a greedy randomized algorithm to minimize the rank of the derived matrix.
Automatic Modulation Recognition of PSK Signals with Sub-Nyquist Sampling Based on High Order Statistics
Venue: arXiv cs.IT 2014
Year: 2014

Sampling rate required in the Nth Power Nonlinear Transformation (NPT) method is typically much greater than Nyquist rate, which causes heavy burden for the Analog to Digital Converter (ADC). Taking advantage of the sparse property of PSK signals' spectrum under NPT, we develop the NPT method for PSK signals with Sub-Nyquist rate samples. In this paper, combined the NPT method with Compressive Sensing (CS) theory, frequency spectrum reconstruction of the Nth power nonlinear transformation of PSK signals is presented, which can be further used for AMR and rough estimations of unknown carrier frequency and symbol rate.
Deep Learning for Multi-label Classification
Venue: arXiv cs.LG 2014
Year: 2014

In multi-label classification, the main focus has been to develop ways of learning the underlying dependencies between labels, and to take advantage of this at classification time. Developing better feature-space representations has been predominantly employed to reduce complexity, e.g., by eliminating non-helpful feature attributes from the input space prior to (or during) training. This is an important task, since many multi-label methods typically create many different copies or views of the same input data as they transform it, and considerable memory can be saved by taking advantage of redundancy. In this paper, we show that a proper development of the feature space can make labels less interdependent and easier to model and predict at inference time. For this task we use a deep learning approach with restricted Boltzmann machines. We present a deep network that, in an empirical evaluation, outperforms a number of competitive methods from the literature
Chinese Interpreting Studies: Genesis of a Discipline
Venue: arXiv cs.DL 2014
Year: 2014

The growth of Chinese Interpreting Studies (CIS) has been robust over the past two decades; this is reflected in the total number of research papers produced. This paper takes a scientometric approach to assessing the production, themes and theoretical influences of those papers over time. The most productive authors, universities, and regions, as well as patterns of research collaboration, were analyzed to gain a deeper understanding of the CIS landscape. This study reveals that the general culture of the discipline remained constant throughout the period, none of its theoretical influences or topics having gained significantly in popularity. However, certain limitations in the way research is conducted (lack of collaboration, inadequate academic policies, etc.) hinder its potential for future growth.
Puzzle: Zermelo-Fraenkel set theory is inconsistent
Venue: arXiv cs.CC 2014
Year: 2014

In this note, we present a puzzle. We prove that Zermelo-Fraenkel set theory is inconsistent by proving, using Zermelo-Fraenkel set theory, the false statement that any algorithm that determines whether any $n \times n$ matrix over $\mathbb F_2$, the finite field of order 2, is nonsingular must run in exponential time in the worst-case scenario. The object of the puzzle is to find the error in the proof.
Google distance between words
Venue: arXiv cs.CL 2015
Year: 2015

Cilibrasi and Vitanyi have demonstrated that it is possible to extract the meaning of words from the world-wide web. To achieve this, they rely on the number of webpages that are found through a Google search containing a given word and they associate the page count to the probability that the word appears on a webpage. Thus, conditional probabilities allow them to correlate one word with another word's meaning. Furthermore, they have developed a similarity distance function that gauges how closely related a pair of words is. We present a specific counterexample to the triangle inequality for this similarity distance function.
Inconsistency Robustness in Logic Programs
Venue: arXiv cs.LO 2015
Year: 2015

Inconsistency robustness is "information system performance in the face of continually pervasive inconsistencies." A fundamental principle of Inconsistency Robustness is to make contradictions explicit so that arguments for and against propositions can be formalized. This paper explores the role of Inconsistency Robustness in the history and theory of Logic Programs. Robert Kowalski put forward a bold thesis: "Looking back on our early discoveries, I value most the discovery that computation could be subsumed by deduction." However, mathematical logic cannot always infer computational steps because computational systems make use of arbitration for determining which message is processed next by a recipient that is sent multiple messages concurrently. Since reception orders are in general indeterminate, they cannot be inferred from prior information by mathematical logic alone. Therefore mathematical logic cannot in general implement computation. Over the course of history, the term "Functional Program" has grown more precise and technical as the field has matured. "Logic Program" should be on a similar trajectory. Accordingly, "Logic Program" should have a general precise characterization. In the fall of 1972, different characterizations of Logic Programs that have continued to this day: * A Logic Program uses Horn-Clause syntax for forward and backward chaining * Each computational step (according to Actor Model) of a Logic Program is deductively inferred (e.g. in Direct Logic). The above examples are illustrative of how issues of inconsistency robustness have repeatedly arisen in Logic Programs.
A Nonlinear Approach to Dimension Reduction
Venue: arXiv cs.CG 2015
Year: 2015

The $l_2$ flattening lemma of Johnson and Lindenstrauss [JL84] is a powerful tool for dimension reduction. It has been conjectured that the target dimension bounds can be refined and bounded in terms of the intrinsic dimensionality of the data set (for example, the doubling dimension). One such problem was proposed by Lang and Plaut [LP01] (see also [GKL03,MatousekProblems07,ABN08,CGT10]), and is still open. We prove another result in this line of work: The snowflake metric $d^{1/2}$ of a doubling set $S \subset l_2$ embeds with constant distortion into $l_2^D$, for dimension $D$ that depends solely on the doubling constant of the metric. In fact, the distortion can be made arbitrarily close to 1, and the target dimension is polylogarithmic in the doubling constant. Our techniques are robust and extend to the more difficult spaces $l_1$ and $l_\infty$, although the dimension bounds here are quantitatively inferior than those for $l_2$.
Randomized Interior Point methods for Sampling and Optimization
Venue: arXiv cs.DS 2015
Year: 2015

We present a Markov chain (Dikin walk) for sampling from a convex body equipped with a self-concordant barrier, whose mixing time from a "central point" is strongly polynomial in the description of the convex set. The mixing time of this chain is invariant under affine transformations of the convex set, thus eliminating the need for first placing the body in an isotropic position. This recovers and extends previous results of from polytopes to more general convex sets. On every convex set of dimension $n$, there exists a self-concordant barrier whose "complexity" is polynomially bounded. Consequently, a rapidly mixing Markov chain of the kind we describe can be defined on any convex set. We use these results to design an algorithm consisting of a single random walk for optimizing a linear function on a convex set. We show that this random walk reaches an approximately optimal point in polynomial time with high probability and that the corresponding objective values converge with probability 1 to the optimal objective value as the number of steps tends to infinity. One technical contribution is a family of lower bounds for the isoperimetric constants of (weighted) Riemannian manifolds on which, interior point methods perform a kind of steepest descent. Using results of Barthe \cite{barthe} and Bobkov and Houdré, on the isoperimetry of products of (weighted) Riemannian manifolds, we obtain sharper upper bounds on the mixing time of Dikin walk on products of convex sets than the bounds obtained from a direct application of the Localization Lemma, on which, since (Lovász and Simonovits), the analyses of all random walks on convex sets have relied.
Geometric Tomography With Topological Guarantees
Venue: arXiv cs.CG 2015
Year: 2015

We consider the problem of reconstructing a compact 3-manifold (with boundary) embedded in $\mathbb{R}^3$ from its cross-sections $\mathcal S$ with a given set of cutting planes $\mathcal P$ having arbitrary orientations. Using the obvious fact that a point $x \in \mathcal P$ belongs to the original object if and only if it belongs to $\mathcal S$, we follow a very natural reconstruction strategy: we say that a point $x \in \mathbb{R}^3$ belongs to the reconstructed object if (at least one of) its nearest point(s) in $\mathcal P$ belongs to $\mathcal S$. This coincides with the algorithm presented by Liu et al. in \cite{LB+08}. In the present paper, we prove that under appropriate sampling conditions, the output of this algorithm preserves the homotopy type of the original object. Using the homotopy equivalence, we also show that the reconstructed object is homeomorphic (and isotopic) to the original object. This is the first time that 3-dimensional shape reconstruction from cross-sections comes with theoretical guarantees.
A unified graphical approach to random coding for multi-terminal networks
Venue: arXiv cs.IT 2015
Year: 2015

A unified approach to the derivation of rate regions for single-hop memoryless networks is presented. A general transmission scheme for any memoryless, single-hop, k-user channel with or without common information, is defined through two steps. The first step is user virtualization: each user is divided into multiple virtual sub-users according to a chosen rate-splitting strategy which preserves the rates of the original messages. This results in an enhanced channel with a possibly larger number of users for which more coding possibilities are available. Moreover, user virtualization provides a simple mechanism to encode common messages to any subset of users. Following user virtualization, the message of each user in the enhanced model is coded using a chosen combination of coded time-sharing, superposition coding and joint binning. A graph is used to represent the chosen coding strategies: nodes in the graph represent codewords while edges represent coding operations. This graph is used to construct a graphical Markov model which illustrates the statistical dependency among codewords that can be introduced by the superposition coding or joint binning. Using this statistical representation of the overall codebook distribution, the error probability of the code is shown to vanish via a unified analysis. The rate bounds that define the achievable rate region are obtained by linking the error analysis to the properties of the graphical Markov model. This proposed framework makes it possible to numerically obtain an achievable rate region by specifying a user virtualization strategy and describing a set of coding operations. The largest achievable rate region can be obtained by considering all the possible rate-splitting strategies and taking the union over all the possible ways to superimpose or bin codewords.
A SWAR Approach to Counting Ones
Venue: arXiv cs.CC 2015
Year: 2015

We investigate the complexity of algorithms counting ones in different sets of operations. With addition and logical operations (but no shift) $O(\log^2(n))$ steps suffice to count ones. Parity can be computed with complexity $O(\log(n))$, which is the same bound as for methods using shift-operations. If multiplication is available, a solution of time complexity $O(\log^*(n))$ is possible improving the known bound $O(\log\log(n))$.
Social choice rules driven by propositional logic
Venue: arXiv cs.AI 2015
Year: 2015

Several rules for social choice are examined from a unifying point of view that looks at them as procedures for revising a system of degrees of belief in accordance with certain specified logical constraints. Belief is here a social attribute, its degrees being measured by the fraction of people who share a given opinion. Different known rules and some new ones are obtained depending on which particular constraints are assumed. These constraints allow to model different notions of choiceness. In particular, we give a new method to deal with approval-disapproval-preferential voting.
Improved integer programming models for simple assembly line balancing and related problems
Venue: arXiv cs.DM 2015
Year: 2015

We propose a stronger formulation of the precedence constraints and the station limits for the simple assembly line balancing problem. The linear relaxation of the improved integer program theoretically dominates all previous formulations using impulse variables, and produces solutions of significantly better quality in practice. The improved formulation can be used to strengthen related problems with similar restrictions. We demonstrate their effectiveness on the U-shaped assembly line balancing problem and on the bin packing problem with precedence constraints.
Lower bounds on the Probability of Error for Classical and Classical-Quantum Channels
Venue: arXiv cs.IT 2015
Year: 2015

In this paper, lower bounds on error probability in coding for discrete classical and classical-quantum channels are studied. The contribution of the paper goes in two main directions: i) extending classical bounds of Shannon, Gallager and Berlekamp to classical-quantum channels, and ii) proposing a new framework for lower bounding the probability of error of channels with a zero-error capacity in the low rate region. The relation between these two problems is revealed by showing that Lovász' bound on zero-error capacity emerges as a natural consequence of the sphere packing bound once we move to the more general context of classical-quantum channels. A variation of Lovász' bound is then derived to lower bound the probability of error in the low rate region by means of auxiliary channels. As a result of this study, connections between the Lovász theta function, the expurgated bound of Gallager, the cutoff rate of a classical channel and the sphere packing bound for classical-quantum channels are established.
Walk-Sums, Continued Fractions and Unique Factorisation on Digraphs
Venue: arXiv cs.DM 2015
Year: 2015

We show that the series of all walks between any two vertices of any (possibly weighted) directed graph $\mathcal{G}$ is given by a universal continued fraction of finite depth and breadth involving the simple paths and simple cycles of $\mathcal{G}$. A simple path is a walk forbidden to visit any vertex more than once. We obtain an explicit formula giving this continued fraction. Our results are based on an equivalent to the fundamental theorem of arithmetic: we demonstrate that arbitrary walks on $\mathcal{G}$ factorize uniquely into nesting products of simple paths and simple cycles, where nesting is a product operation between walks that we define. We show that the simple paths and simple cycles are the prime elements of the set of all walks on $\mathcal{G}$ equipped with the nesting product. We give an algorithm producing the prime factorization of individual walks, and obtain a recursive formula producing the prime factorization of sets of walks. Our results have already found applications in machine learning, matrix computations and quantum mechanics.
Constant-Optimized Quantum Circuits for Modular Multiplication and Exponentiation
Venue: arXiv cs.ET 2015
Year: 2015

Reversible circuits for modular multiplication $Cx$%$M$ with $x<M$ arise as components of modular exponentiation in Shor's quantum number-factoring algorithm. However, existing generic constructions focus on asymptotic gate count and circuit depth rather than actual values, producing fairly large circuits not optimized for specific $C$ and $M$ values. In this work, we develop such optimizations in a bottom-up fashion, starting with most convenient $C$ values. When zero-initialized ancilla registers are available, we reduce the search for compact circuits to a shortest-path problem. Some of our modular-multiplication circuits are asymptotically smaller than previous constructions, but worst-case bounds and average sizes remain $Θ(n^2)$. In the context of modular exponentiation, we offer several constant-factor improvements, as well as an improvement by a constant additive term that is significant for few-qubit circuits arising in ongoing laboratory experiments with Shor's algorithm.
On the system CL12 of computability logic
Venue: arXiv cs.LO 2015
Year: 2015

Computability logic (see http://www.csc.villanova.edu/~japaridz/CL/) is a long-term project for redeveloping logic on the basis of a constructive game semantics, with games seen as abstract models of interactive computational problems. Among the fragments of this logic successfully axiomatized so far is CL12 --- a conservative extension of classical first-order logic, whose language augments that of classical logic with the so called choice sorts of quantifiers and connectives. This system has already found fruitful applications as a logical basis for constructive and complexity-oriented versions of Peano arithmetic, such as arithmetics for polynomial time computability, polynomial space computability, and beyond. The present paper introduces a third, indispensable complexity measure for interactive computations termed amplitude complexity, and establishes the adequacy of CL12 with respect to A-amplitude, S-space and T-time computability under certain minimal conditions on the triples (A,S,T) of function classes. This result very substantially broadens the potential application areas of CL12. The paper is self-contained, and targets readers with no prior familiarity with the subject.
A Digital Signature Scheme for Long-Term Security
Venue: arXiv cs.CR 2015
Year: 2015

In this paper we propose a signature scheme based on two intractable problems, namely the integer factorization problem and the discrete logarithm problem for elliptic curves. It is suitable for applications requiring long-term security and provides a more efficient solution than the existing ones.
Kernelizing MSO Properties of Trees of Fixed Height, and Some Consequences
Venue: arXiv cs.DM 2015
Year: 2015

Fix an integer h>=1. In the universe of coloured trees of height at most h, we prove that for any graph decision problem defined by an MSO formula with r quantifiers, there exists a set of kernels, each of size bounded by an elementary function of r and the number of colours. This yields two noteworthy consequences. Consider any graph class G having a one-dimensional MSO interpretation in the universe of coloured trees of height h (equivalently, G is a class of shrub-depth h). First, class G admits an MSO model checking algorithm whose runtime has an elementary dependence on the formula size. Second, on G the expressive powers of FO and MSO coincide (which extends a 2012 result of Elberfeld, Grohe, and Tantau).
Finite-time Convergent Gossiping
Venue: arXiv cs.DC 2015
Year: 2015

Gossip algorithms are widely used in modern distributed systems, with applications ranging from sensor networks and peer-to-peer networks to mobile vehicle networks and social networks. A tremendous research effort has been devoted to analyzing and improving the asymptotic rate of convergence for gossip algorithms. In this work we study finite-time convergence of deterministic gossiping. We show that there exists a symmetric gossip algorithm that converges in finite time if and only if the number of network nodes is a power of two, while there always exists an asymmetric gossip algorithm with finite-time convergence, independent of the number of nodes. For $n=2^m$ nodes, we prove that a fastest convergence can be reached in $nm=n\log_2 n$ node updates via symmetric gossiping. On the other hand, under asymmetric gossip among $n=2^m+r$ nodes with $0\leq r<2^m$, it takes at least $mn+2r$ node updates for achieving finite-time convergence. It is also shown that the existence of finite-time convergent gossiping often imposes strong structural requirements on the underlying interaction graph. Finally, we apply our results to gossip algorithms in quantum networks, where the goal is to control the state of a quantum system via pairwise interactions. We show that finite-time convergence is never possible for such systems.
Continuous Time Dynamic Topic Models
Venue: arXiv cs.IR 2015
Year: 2015

In this paper, we develop the continuous time dynamic topic model (cDTM). The cDTM is a dynamic topic model that uses Brownian motion to model the latent topics through a sequential collection of documents, where a "topic" is a pattern of word use that we expect to evolve over the course of the collection. We derive an efficient variational approximate inference algorithm that takes advantage of the sparsity of observations in text, a property that lets us easily handle many time points. In contrast to the cDTM, the original discrete-time dynamic topic model (dDTM) requires that time be discretized. Moreover, the complexity of variational inference for the dDTM grows quickly as time granularity increases, a drawback which limits fine-grained discretization. We demonstrate the cDTM on two news corpora, reporting both predictive perplexity and the novel task of time stamp prediction.